R Notebook

    library(readr); library(dplyr); library(stringr); library(lubridate)

Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union


Attaching package: ‘lubridate’

The following object is masked from ‘package:base’:

    date

plasticContainer <- list(
  greenBox=c("paper","scissor"),     # location 1
  redBox=c(1L,3L,2.5),               # location 2
  blueBox=c(TRUE,FALSE,TRUE,TRUE)    # location 3
)

plasticContainer[c("greenBox")] # or plasticContainer[c(1,2)]

$greenBox
[1] "paper"   "scissor"

plasticContainer[["greenBox"]] # or plasticContainer[[1]]

[1] "paper"   "scissor"

plasticContainer$greenBox

[1] "paper"   "scissor"

#如果上面要取出paper，請問要怎麼延伸拿取？ans1
plasticContainer[["greenBox"]][1]

[1] "paper"

#如果上面要取出paper，請問要怎麼延伸拿取？ans2
plasticContainer$greenBox[1]

[1] "paper"

#如果上面要取出paper，請問要怎麼延伸拿取？wrong version
plasticContainer["greenBox"][1] #1是指greenbox

$greenBox
[1] "paper"   "scissor"

#如果上面要取出paper，請問要怎麼延伸拿取？ans3
plasticContainer["greenBox"]$greenBox[1]

[1] "paper"

#如果上面要取出paper，請問要怎麼延伸拿取？ans4
plasticContainer["greenBox"][["greenBox"]][1]

[1] "paper"

我是分隔線

    install.packages("plotly")

  There is a binary version available but the source version
  is later:

installing the source package ‘plotly’

嘗試 URL 'https://cran.rstudio.com/src/contrib/plotly_4.8.0.tar.gz'
Content type 'application/x-gzip' length 1860673 bytes (1.8 MB)
==================================================
downloaded 1.8 MB

* installing *source* package ‘plotly’ ...
** package ‘plotly’ successfully unpacked and MD5 sums checked
** R
** data
*** moving datasets to lazyload DB
** demo
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
*** copying figures
** building package indices
** testing if installed package can be loaded
* DONE (plotly)

The downloaded source packages are in
    ‘/private/var/folders/xv/58tq8zqs5w59jnft9dljvy6h0000gn/T/RtmpupeV3Z/downloaded_packages’

download.file("https://github.com/tpemartin/github-data/blob/master/plotly_4070_neda.Rda?raw=true",destfile = "plotly_4070_neda.Rda")

嘗試 URL 'https://github.com/tpemartin/github-data/blob/master/plotly_4070_neda.Rda?raw=true'
Content type 'application/octet-stream' length 12400 bytes (12 KB)
==================================================
downloaded 12 KB

load("plotly_4070_neda.Rda")
library(plotly)

Loading required package: ggplot2

Attaching package: ‘plotly’

The following object is masked from ‘package:ggplot2’:

    last_plot

The following object is masked from ‘package:stats’:

    filter

The following object is masked from ‘package:graphics’:

    layout

plotly_4070_neda

plotly_4070_neda$x$layout$shapes[[1]]$opacity

[1] 0.2

plotly_4070_neda$x$layout$shapes[[1]]$opacity <- 0.8
plotly_4070_neda

我是分隔線

library(readr); library(dplyr); library(stringr); library(lubridate)

library(readr)
transcriptData <- read_csv("https://raw.githubusercontent.com/tpemartin/github-data/master/transcript100_102.csv",
                  col_types = cols(
                    學期成績="n"
                  ))
totalCredits<-function(x){
  transcriptData[transcriptData$學號==x,]->subsample 
  subsample %>%
    mutate(
      及格=(學期成績>=60)
    ) %>%
    summarise(
      學號=學號[1],
      總修習學分數=sum(學分數),
      總實得學分數=sum(學分數[及格])
    )  
}

transcriptData %>%
  filter(學屆==100,str_sub(學號,5,6)=="P1") -> subsample
subsample$學號 %>% unique -> 符合條件學號

creditResults<-vector("list",length(符合條件學號))
for(i in seq_along(符合條件學號)){
  creditResults[[i]] <- totalCredits(符合條件學號[i])
}

分隔

library(readr)
library(tidyr)
libraryData <- read_csv("https://raw.githubusercontent.com/tpemartin/github-data/master/libraryData2.csv")

Parsed with column specification:
cols(
  學號 = col_character(),
  書籍類別 = col_character(),
  書籍名稱 = col_character(),
  書籍出版日期 = col_integer(),
  書籍館藏地 = col_character(),
  書籍上架年月 = col_date(format = ""),
  入學年 = col_integer(),
  讀者年級 = col_integer(),
  學院 = col_character(),
  借閱時間 = col_datetime(format = ""),
  學期 = col_integer(),
  學年 = col_integer(),
  學系 = col_character()
)

libraryData %>%
  group_by(學院) %>%
  nest(.key="各院借閱資料") ->
  libraryDataNested

library(dplyr)
libraryData %>%
  filter(學院=="人文學院")

df <- data.frame(
  x = 1:3,
  y = c("a", "d,e,f", "g,h"),
  z = c("A","A","B"),
  stringsAsFactors = F
)
df %>% 
  group_by(z) %>%
  nest -> dfNested